IQ’s Corner: J. Intell. | Free Full-Text

 J. Intell. | Free Full-Text | Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners

Abstract: Network analytic methods that are ubiquitous in other areas, such as systems neuroscience,

have recently been used to test network theories in psychology, including intelligence research.

The network or mutualism theory of intelligence proposes that the statistical associations among

cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations

among them throughout development. In this study, we used network models (specifically LASSO)

of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model

brain–behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical

volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5–18) cohort of struggling

learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive,

neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and

calculating node centrality (absolute strength and bridge strength), we found convergent evidence

that subsets of both cognitive and neural nodes play an intermediary role ‘between’ brain and

behavior. We discuss implications and possible avenues for future studies.

Keywords: general intelligence; cortical volume; fractional anisotropy; brain structural covariance;

cognitive network neuroscience; multilayer network analysis


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